caa a22 4500 475793250 CHVBK 20180406123716.0 cr unu---uuuuu 170329e20000801xx s 000 0 eng 10.1007/s001840000055 doi (NATIONALLICENCE)springer-10.1007/s001840000055 Dahlhaus Rainer Universität Heidelberg, Institut für Angewandte Mathematik, Im Neuenheimer Feld 294, 69120 Heidelberg, Germany (e-mail: dahlhaus@statlab.uni-heidelberg.de), DE aut Graphical interaction models for multivariate time series1 [Elektronische Daten] [Rainer Dahlhaus] Abstract.: In this paper we extend the concept of graphical models for multivariate data to multivariate time series. We define a partial correlation graph for time series and use the partial spectral coherence between two components given the remaining components to identify the edges of the graph. As an example we consider multivariate autoregressive processes. The method is applied to air pollution data. Springer-Verlag Berlin Heidelberg, 2000 Key words: Graphical models, multivariate time series, partial spectral coherence, spectral estimates, multivariate autoregressive processes, air pollution data nationallicence https://doi.org/10.1007/s001840000055 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s001840000055 text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Dahlhaus Rainer Universität Heidelberg, Institut für Angewandte Mathematik, Im Neuenheimer Feld 294, 69120 Heidelberg, Germany (e-mail: dahlhaus@statlab.uni-heidelberg.de), DE aut Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer